• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.123-130
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• 2007

The aim of this study was to propose a fusion and registration method with heterogeneous small animal acquisition system in small animal in-vivo study. After an intravenous injection of $^{18}F$-FDG through tail vain and 60 min delay for uptake, mouse was placed on an acryl plate with fiducial markers that were made for fusion between small animal PET (microPET R4, Concorde Microsystems, Knoxville TN) and Discovery LS CT images. The acquired emission list-mode data was sorted to temporally framed sinograms and reconstructed using FORE rebining and 2D-OSEM algorithms without correction of attenuation and scatter. After PET imaging, CT images were acquired by mean of a clinical PET/CT with high-resolution mode. The microPET and CT images were fusion and co-registered using the fiducial markers and segmented lung region in both data sets to perform a point-based rigid co-registration. This method improves the quantitative accuracy and interpretation of the tracer.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.28-34
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• 2020

This paper proposes an approach to the fusion of two heterogeneous sensors with two different fields-of-view (FOV): LIDAR and an RGB camera. Registration between data captured by LIDAR and an RGB camera provided the fusion results. Registration was completed once a depthmap corresponding to a 2-dimensional RGB image was generated. For this fusion, RPLIDAR-A3 (manufactured by Slamtec) and a general digital camera were used to acquire depth and image data, respectively. LIDAR sensor provided distance information between the sensor and objects in a scene nearby the sensor, and an RGB camera provided a 2-dimensional image with color information. Fusion of 2D image and depth information enabled us to achieve better performance with applications of object detection and tracking. For instance, automatic driver assistance systems, robotics or other systems that require visual information processing might find the work in this paper useful. Since the LIDAR only provides depth value, processing and generation of a depthmap that corresponds to an RGB image is recommended. To validate the proposed approach, experimental results are provided.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4290-4309
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• 2020

In recent years, advancements in machine learning capabilities have allowed it to see widespread adoption for tasks such as object detection, image classification, and anomaly detection. However, despite their promise, a limitation lies in the fact that a network's performance quality is based on the data which it receives. A well-trained network will still have poor performance if the subsequent data supplied to it contains artifacts, out of focus regions, or other visual distortions. Under normal circumstances, images of the same scene captured from differing points of focus, angles, or modalities must be separately analysed by the network, despite possibly containing overlapping information such as in the case of images of the same scene captured from different angles, or irrelevant information such as images captured from infrared sensors which can capture thermal information well but not topographical details. This factor can potentially add significantly to the computational time and resources required to utilize the network without providing any additional benefit. In this study, we plan to explore using image fusion techniques to assemble multiple images of the same scene into a single image that retains the most salient key features of the individual source images while discarding overlapping or irrelevant data that does not provide any benefit to the network. Utilizing this image fusion step before inputting a dataset into the network, the number of images would be significantly reduced with the potential to improve the classification performance accuracy by enhancing images while discarding irrelevant and overlapping regions.

• Smart Structures and Systems
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• v.16 no.2
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• pp.295-328
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• 2015

In recent years the monitoring of structural behavior through acquisition of vibrational data has become common practice. In addition, recent advances in sensor development have made the collection of diverse dynamic information feasible. Other than the commonly collected acceleration information, Global Position System (GPS) receivers and non-contact, optical techniques have also allowed for the synchronous collection of highly accurate displacement data. The fusion of this heterogeneous information is crucial for the successful monitoring and control of structural systems especially when aiming at real-time estimation. This task is not a straightforward one as measurements are inevitably corrupted with some percentage of noise, often leading to imprecise estimation. Quite commonly, the presence of noise in acceleration signals results in drifting estimates of displacement states, as a result of numerical integration. In this study, a new approach based on a time domain identification method, namely the Unscented Kalman Filter (UKF), is proposed for correcting the "drift effect" in displacement or rotation estimates in an online manner, i.e., on the fly as data is attained. The method relies on the introduction of artificial white noise (WN) observations into the filter equations, which is shown to achieve an online correction of the drift issue, thus yielding highly accurate motion data. The proposed approach is demonstrated for two cases; firstly, the illustrative example of a single degree of freedom linear oscillator is examined, where availability of acceleration measurements is exclusively assumed. Secondly, a field inspired implementation is presented for the torsional identification of a tall tower structure, where acceleration measurements are obtained at a high sampling rate and non-collocated GPS displacement measurements are assumed available at a lower sampling rate. A multi-rate Kalman Filter is incorporated into the analysis in order to successfully fuse data sampled at different rates.

• Journal of the Korea Convergence Society
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• v.7 no.3
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• pp.35-44
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• 2016

The purpose of this study is to examine the theoretical background of art make-up and surrealism in depth and shed new light on creative thoughts coming through application of Depaysement and various kinds of expression realized through art make-up, where art and make-up are incorporated. The study method is to conduct prior research followed by a theoretical study of the concept and techniques of Surrealistic Depaysement and theoretical background of art make-up through specialized books and internet sources and then to create 4 artworks representing characteristics of Depaysement technique categorized in dual image, fusion of heterogeneous objects, modification and conversion, and change of space. This examination resulted in first, a foundational ground for fusion and use of art and make-up sectors by creating a realm of expression based on creativity through incorporation of art and makeup and second, a sense of freshness and unfamiliar-ness by creation of an image in a completely unfamiliar space. Therefore, the researcher sets a direction for ways to come up with new ideas and expand the realm of expression and hopes that the art-makeup does not just become an aesthetic tool but turn itself as an art genre.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.2
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• pp.677-684
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• 2016

Background: Acute lymphoblastic leukemia (ALL) is a heterogeneous disease which requires a risk-stratified approach for appropriate treatment. Specific chromosomal translocations within leukemic blasts are important prognostic factors that allow identification of relevant subgroups. In this study, we developed a multiplex RT-PCR assay for detection of the 4 most frequent translocations in ALL (BCR-ABL, TEL-AML1, MLL-AF4, and E2A-PBX1). Materials and Methods: A total of 214 diagnosed ALL samples from both adult and pediatric ALL and 14 cases of CML patients (154 bone marrow and 74 peripheral blood samples) were assessed for specific chromosomal translocations by cytogenetic and multiplex RT-PCR assays. Results: The results showed that 46 cases of ALL and CML (20.2%) contained the fusion transcripts. Within the positive ALL patients, the most prevalent cryptic translocation observed was mBCR-ABL (p190) at 8.41%. In addition, other genetic rearrangements detected by the multiplex PCR were 4.21% TEL-AML1 and 2.34% E2A-PBX1, whereas MLL-AF4 exhibited negative results in all tested samples. Moreover, MBCR-ABL was detected in all 14 CML samples. In 16 samples of normal karyotype ALL (n=9), ALL with no cytogentic result (n=4) and CML with no Philadelphia chromosome (n=3), fusion transcripts were detected. Conclusions: Multiplex RT-PCR provides a rapid, simple and highly sensitive method to detect fusion transcripts for prognostic and risk stratification of ALL and CML patients.

• Applied Chemistry for Engineering
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• v.26 no.6
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• pp.743-745
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• 2015

Amorphous cobalt phosphates were synthesized with their distinct morphology by controlling the amount of base in the synthetic condition. The crystallinity and morphology of cobalt phosphates were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM). The prepared cobalt phosphates were applied as a heterogeneous catalyst for generating hydrogen gas from the hydrolysis reaction of sodium borohydride. We found that the catalyst prepared using the least amount of base condition at room temperature showed a plate shape with less than 10 nm thickness, which resulted in the best catalytic activity among all catalysts due to the large surface area.

• ETRI Journal
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• v.42 no.6
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• pp.886-898
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• 2020

Unusual data patterns or outliers can be generated because of human errors, incorrect measurements, or malicious activities. Detecting outliers is a difficult task that requires complex ensembles. An ideal outlier detection ensemble should consider the strengths of individual base detectors while carefully combining their outputs to create a strong overall ensemble and achieve unbiased accuracy with minimal variance. Selecting and combining the outputs of dissimilar base learners is a challenging task. This paper proposes a model that utilizes heterogeneous base learners. It adaptively boosts the outcomes of preceding learners in the first phase by assigning weights and identifying high-performing learners based on their local domains, and then carefully fuses their outcomes in the second phase to improve overall accuracy. Experimental results from 10 benchmark datasets are used to train and test the proposed model. To investigate its accuracy in terms of separating outliers from inliers, the proposed model is tested and evaluated using accuracy metrics. The analyzed data are presented as crosstabs and percentages, followed by a descriptive method for synthesis and interpretation.

• International journal of advanced smart convergence
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• v.9 no.1
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• pp.109-112
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• 2020

Many devices are connected on the internet to give functionalities for interconnected services. In 2020', The number of devices connected to the internet will be reached 5.8 billion. Moreover, many connected service provider such as Google and Amazon, suggests edge computing and mesh networks to cope with this situation which the many devices completely connected on their networks. This paper introduces the current state of the introduction of the wireless mesh network and edge cloud in order to efficiently manage a large number of nodes in the exploding Internet of Things (IoT) network and introduces the existing Network Time Protocol (NTP). On the basis of this, we propose a relatively accurate time synchronization method, especially in heterogeneous mesh networks. Using this NTP, multiple time coordinators can be placed in a mesh network to find the delay error using the average delay time and the delay time of the time coordinator. Therefore, accurate time can be synchronized when implementing IoT, remote metering, and real-time media streaming using IoT mesh network.

• Journal of Welding and Joining
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• v.28 no.2
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• pp.47-53
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• 2010

According to the research report for the recent a few years, the dissimilar welding of Cu and STS 304 alloy have been presented that a weldability is very poor. This article present a study on Lap joint by Electron beam welding dissimilar materials. The weld metals was constituted between pure copper and STS 304 steel. The experiment was performed with 125mA welding current, 520mA focusing current. The Vacuum condition of chamber is 5${\times}$10-5torr and welding speed is 300mm/min. Showing the bead shape of weld metal, the thickness of the stainless 304 using as the protect materials is 3mm and the thickness of a copper is 15mm. The analysis about the microstructure were carried out in which it was observed with SEM. The results showed that complex heterogeneous fusion zone microstructure characterized both by rapid cooling and mixing of the molten metal, however the liquation crack was formated in the fusion line.